dag

Tools for converting between directed acyclic graphs (DAGs) and quantum circuits

Functions:

Name	Description
draw_dag	Draws a directed acyclic graph (DAG) representation of a quantum circuit and saves it as an image.
qc2dag	Converts a quantum circuit into a directed acyclic graph (DAG).
dag2qc	Converts a directed acyclic graph (DAG) back into a QuantumCircuit.

draw_dag(dag, output='dag_figure.png')

Draws a directed acyclic graph (DAG) representation of a quantum circuit and saves it as an image.

Parameters:

Name	Type	Description	Default
dag	DiGraph	The quantum circuit represented as a directed acyclic graph.	required
output	str	The filename for saving the generated DAG image. Defaults to 'dag_figure.png'.	'dag_figure.png'

Source code in quark/circuit/dag.py

def draw_dag(dag, output='dag_figure.png'):
    """Draws a directed acyclic graph (DAG) representation of a quantum circuit and saves it as an image.

    Args:
        dag (nx.DiGraph): The quantum circuit represented as a directed acyclic graph.
        output (str, optional): The filename for saving the generated DAG image. Defaults to 'dag_figure.png'.
    """
    import matplotlib.pyplot as plt

    A = nx.nx_agraph.to_agraph(dag)

    for node in A.nodes():
        gate = node.split('_')[0]
        if gate == 'measure':
            cbit = dag.nodes[node]['cbits'][0]
            node.attr['label'] = gate + f' [c{cbit}]'
        else:
            node.attr['label'] = gate
    for u, v, data in dag.edges(data=True):
        edge = A.get_edge(u, v)
        line = ''
        for qubit in data['qubit']:
            line += 'q'+str(qubit)
        edge.attr['label'] = line #data['qubit'] 

    A.graph_attr['dpi'] = '300' 
    A.layout(prog='dot')

    A.draw(output)

    img = plt.imread(output)
    plt.imshow(img)
    plt.axis('off')
    plt.show()

qc2dag(qc: QuantumCircuit, show_qubits: bool = True) -> nx.DiGraph

Converts a quantum circuit into a directed acyclic graph (DAG).

Parameters:

Name	Type	Description	Default
qc	QuantumCircuit	The quantum circuit to be converted.	required

Returns:

Type	Description
DiGraph	nx.DiGraph: A directed acyclic graph representing the quantum circuit,
DiGraph	with nodes as operations and edges as dependencies.

Source code in quark/circuit/dag.py

def qc2dag(qc: 'QuantumCircuit',show_qubits:bool=True) -> 'nx.DiGraph':
    """Converts a quantum circuit into a directed acyclic graph (DAG).

    Args:
        qc (QuantumCircuit): The quantum circuit to be converted.

    Returns:
        nx.DiGraph: A directed acyclic graph representing the quantum circuit, 
        with nodes as operations and edges as dependencies.
    """
    node_list,edge_list = convert_gate_info_to_dag_info(qc.nqubits,qc.qubits,qc.gates,show_qubits=show_qubits)
    dag = nx.DiGraph()
    dag.add_nodes_from(node_list)
    dag.add_edges_from(edge_list)
    dag.graph['qubits'] = qc.qubits
    return dag

dag2qc(dag: nx.DiGraph, nqubits: int | None = None, ncbits: int | None = None) -> QuantumCircuit

Converts a directed acyclic graph (DAG) back into a QuantumCircuit.

Parameters:

Name	Type	Description	Default
dag	DiGraph	The DAG representation of the quantum circuit.	required
nqubits	int	The number of qubits in the circuit.	None
ncbits	int | None	The number of classical bits in the circuit. Defaults to the value of nqubits.	None

Returns:

Name	Type	Description
QuantumCircuit	QuantumCircuit	The reconstructed quantum circuit based on the DAG structure.

Source code in quark/circuit/dag.py

def dag2qc(dag: 'nx.DiGraph',nqubits: int|None=None, ncbits: int|None = None) -> 'QuantumCircuit':
    """Converts a directed acyclic graph (DAG) back into a QuantumCircuit.

    Args:
        dag (nx.DiGraph):The DAG representation of the quantum circuit.
        nqubits (int): The number of qubits in the circuit.
        ncbits (int | None, optional): The number of classical bits in the circuit. Defaults to the value of `nqubits`.

    Returns:
        QuantumCircuit: The reconstructed quantum circuit based on the DAG structure.
    """
    current_qubits = []    
    new = []
    for node in nx.topological_sort(dag):
        gate = node.split('_')[0]
        qubits = dag.nodes[node]['qubits']
        current_qubits += qubits
        #print(gate,qubits)
        if gate in one_qubit_gates_available.keys():
            new.append((gate,qubits[0]))
        elif gate in two_qubit_gates_available.keys():
            new.append((gate,qubits[0],qubits[1]))
        elif gate in three_qubit_gates_available.keys():
            new.append((gate,qubits[0],qubits[1],qubits[2]))
        elif gate in one_qubit_parameter_gates_available.keys():
            params = dag.nodes[node]['params']
            new.append((gate,*params,qubits[0]))
        elif gate in two_qubit_parameter_gates_available.keys():
            params = dag.nodes[node]['params']
            new.append((gate,*params,qubits[0],qubits[1]))
        elif gate in functional_gates_available.keys():
            if gate == 'measure':
                cbits = dag.nodes[node]['cbits']
                new.append((gate,qubits,cbits))
            elif gate == 'barrier':
                new.append((gate,tuple(qubits)))
            elif gate == 'delay':
                duration = dag.nodes[node]['duration']
                new.append((gate,duration,tuple(qubits)))
            elif gate == 'reset':
                new.append((gate,qubits[0]))
    if nqubits is None:
        nqubits = max(current_qubits)+1
    if ncbits is None:
        ncbits = nqubits                
    qc = QuantumCircuit(nqubits, ncbits)
    qc.gates = new
    qc.qubits = dag.graph['qubits']
    return qc